The focus of this project is to understand the computational role of eye movements, hand movements, and short-term memory in natural tasks. The eye and hand tracking equipment, in conjunction with virtual reality displays, is used to delineate the trade-offs between eye movements, head movements, and memory use. The limited nature of human working memory has been taken as a kind of explanatory primitive in understanding cognitive processes. However, there has been surprisingly little effort directed at understanding why it is limited, and how these limitations play themselves out in normal behavior. This research has suggested why working memory is limited. The `active vision' approach has led to a computational model of working memory. In this model there is a real advantage to be gained by such a system in terms of simplifying the underlying cortical decision-making processes and minimizing the need for central executive control. To this end the central focus of this project is to implement a complete, constructive model of behavioral tasks on robotic hardware. A better understanding of how the system works as a whole should provide better guidance in how to approach the underlying neural organization.